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6.0 - 10.0 years

0 Lacs

karnataka

On-site

The role requires you to design, develop, and maintain complex, high-performance, and scalable MLOps systems that interact with AI models and systems. You will collaborate with cross-functional teams, including data scientists, AI researchers, and AI/ML engineers, to comprehend requirements, define project scope, and ensure alignment with business goals. Your expertise will be crucial in selecting, evaluating, and implementing software technologies, tools, and frameworks within a cloud-native (Azure + AML) environment. Troubleshooting and resolving intricate software issues to ensure optimal performance and reliability when interfacing with AI/ML systems is an essential part of your responsibilities. Additionally, you will contribute to software development project planning and estimation, ensuring efficient resource allocation and timely solution delivery. Your role involves contributing to the development of continuous integration and continuous deployment (CI/CD) pipelines, high-performance data pipelines, storage systems, and data processing solutions. You will drive the integration of GenAI models, such as LLMs and foundation models, into production workflows, including overseeing orchestration and evaluation pipelines. Moreover, you will provide support for edge deployment use cases through model optimization, conversion (e.g., to ONNX, TFLite), and containerization for edge runtimes. Your contribution to creating and maintaining technical documentation, including design specifications, API documentation, data models, data flow diagrams, and user manuals, will be vital for effective communication within the team. **Required Qualifications:** - Bachelor's degree in software engineering/computer science or related discipline - Minimum of 6 years of experience in machine learning operations or software/platform development - Strong familiarity with Azure ML, Azure DevOps, Blob Storage, and containerized model deployments on Azure - Proficiency in programming languages commonly used in AI/ML, such as Python, R, or C++ - Experience with Azure cloud platform, machine learning services, and industry best practices **Preferred Qualifications:** - Experience with machine learning frameworks like TensorFlow, PyTorch, or Keras - Familiarity with version control systems like Git and CI/CD tools such as Jenkins, GitLab CI/CD, or Azure DevOps - Knowledge of containerization technologies such as Docker and Kubernetes, along with infrastructure-as-code tools like Terraform or Azure Resource Manager (ARM) templates - Exposure to Generative AI workflows, including prompt engineering, LLM fine-tuning, or retrieval-augmented generation (RAG) - Understanding of GenAI frameworks like LangChain, LlamaIndex, Hugging Face Transformers, and OpenAI API integration - Experience in deploying optimized models on edge devices using ONNX Runtime, TensorRT, OpenVINO, or TFLite - Hands-on experience with monitoring LLM outputs, feedback loops, or LLMOps best practices - Familiarity with edge inference hardware such as NVIDIA Jetson, Intel Movidius, or ARM Cortex-A/NPU devices This is a permanent position requiring in-person work.,

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